Systems and methods for managing sleep quality of a patient, comprising: collecting physiological signal data of the patient using a data acquisition unit electrically coupled to at least one sensor affixed to the patient that generates the physiologic signal data; using one or more hardware processors executing instructions stored in a storage device: filtering the physiological signal data into a plurality of frequency bands corresponding to a plurality of power spectra waveforms; and characterizing an etiology of sleep quality of the patient based on a comparison of at least a first power spectra waveform of the plurality of power spectra waveforms against at least a second power spectra waveform of the plurality of power spectra waveforms, wherein the sleep quality of the patient is managed based on the characterized etiology of sleep.

A bio-signal measurement apparatus comprises tool-less connectors, coupling targets, a controllable coupling selection arrangement, and a control arrangement. The tool-less connectors are for an electric contact with a separate docking apparatus or an electrode arrangement. The coupling targets include a battery and a data communication unit that performs electrically a plug-and-play data transfer with the separate docking apparatus. The tool-less connectors, the number of which is three, are electrically coupled with the controllable coupling selection arrangement, which electrically couples all the tool-less connectors with only one of the coupling targets at a time in response to control from the control arrangement. The battery receives electricity from the tool-less connectors for charging the battery through the electric coupling caused by the coupling selection arrangement under control of the control arrangement during a first time window when the bio-signal measurement apparatus is connected with the docking apparatus. The data communication unit sends and/or receives data through the tool-less connectors using the plug-and-play data transfer based on the electric coupling caused by the coupling selection arrangement under control of the control arrangement during a second time window when the bio-signal measurement apparatus is connected with the docking apparatus.

A sound processing system measures one or more periauricular muscle signals from one or more periauricular muscles of a user. Additionally, the sound processing system computes, based on the periauricular muscle signals, an estimate of an angle corresponding to a direction of a current auditory attention locus of the user with respect to a reference point or plane. The sound processing system controls, based on the estimate of the angle, an operating characteristic of the sound processing system.

The present invention provides a method of conducting a sleep analysis by collecting physiologic and kinetic data from a subject, preferably via a wireless in-home data acquisition system, while the subject attempts to sleep at home. The sleep analysis, including clinical and research sleep studies and cardiorespiratory studies, can be used in the diagnosis of sleeping disorders and other diseases or conditions with sleep signatures, such as Parkinson's, epilepsy, chronic heart failure, chronic obstructive pulmonary disorder, or other neurological, cardiac, pulmonary, or muscular disorders. The method of the present invention can also be used to determine if environmental factors at the subject's home are preventing restorative sleep.

A biosignal-based avatar control system according to an embodiment of the present disclosure includes an avatar generating unit that generates a user's avatar in a virtual reality environment, a biosignal measuring unit that measures the user's biosignal using a sensor, a command determining unit that determines the user's command based on the measured biosignal, an avatar control unit that controls the avatar to perform the command, an output unit that outputs an image of the avatar in real-time, and a protocol generating unit for generating a protocol that provides predetermined tasks, and determines if the avatar performed the predetermined tasks. According to an embodiment of the present disclosure, it is possible to provide feedback in real-time by understanding the user's intention through analysis of biosignals and controlling the user's avatar in a virtual reality environment, thereby improving the user's brain function and motor function.

Provided is a data processing apparatus including a signal data processor configured to collect signal data detected through polysomnography, to extract feature data by analyzing a feature of the collected signal data, and to transform the extracted feature data to time series data; and a sleep stage classification model processor configured to input the processed signal data to a pre-generated sleep stage classification model, and to classify a sleep stage corresponding to the signal data. The signal data processor is configured to extract feature data by analyzing a feature of each of an electroencephalographic (EEG) signal, an electro-oculographic (EOG) signal, and an electromyographic (EMG) signal with respect to the signal data, and to transform the extracted feature data to an epoch unit of time series data to input the extracted feature data to the pre-generated sleep stage classification model.

The present disclosure provides methods for preventing or treating ocular diseases such as diabetic retinopathy and diabetic macular edema, wherein the methods include administering non-invasive photobiomodulation light therapy comprising a light having a wavelength in a red wavelength range. Biomarkers and diagnostic assays for selecting a treatment are also provided.

Provided is an automatic determination apparatus using a deep learning, the automatic determination apparatus including a signal data processor configured to collect signal data detected through polysomnography, to extract feature data by analyzing a feature of the collected signal data, and to transform the extracted feature data to time series data; and a sleep stage classification model processor configured to input the processed signal data to a pre-generated sleep stage classification model, and to classify a sleep stage corresponding to the signal data. The sleep stage classification model processor is configured to classify the sleep stage based on at least one of an American Academy of Sleep Medicine (AASM) standard and a Rechtschaffen and Kales (R&K) standard using an epoch unit of time series data as the processed signal data.

A method and apparatus for performing a biosignal analysis task using a set of models includes receiving an input biosignal. Information that identifies the biosignal analysis task to be performed in association with the input biosignal is received. A waveform model and a digital signal processing (DSP) model are selected. A first type of feature and a second type of feature of the input biosignal are identified. An analysis model is selected, and the biosignal analysis task is performed using the analysis model.

The present invention discloses a brain stimulation systems, devices and methods to: induce lucid reality; improve sleep; improve motor performance; improve learning; enhance gaming activities; improve mental health; and any combination thereof. The system comprises at least one head mounted device; at least one power supply unit; at least one communication unit; at least one microcontroller; at least one external device; and at least one cloud-based storing device.